Industrial agents in the era of service-oriented architectures and cloudbased industrial infrastructures

The umbrella paradigm underpinning novel collaborative industrial systems is to consider the set of intelligent system units as a conglomerate of distributed, autonomous, intelligent, proactive, fault-tolerant, and reusable units, which operate as a set of cooperating entities (Colombo and Karnouskos, 2009). These entities are forming an evolvable infrastructure, entering and/or going out (plug-in/plugout) in an asynchronous manner. Moreover, these entities, having each of them their own functionalities, data, and associated information are now connected and able to interact. They are capable of working in a proactive manner, initiating collaborative actions and dynamically interacting with each other in order to achieve both local and global objectives.info:eu-repo/semantics/publishedVersio

A Knowledge Graph Based Integration Approach for Industry 4.0

The fourth industrial revolution, Industry 4.0 (I40) aims at creating smart factories employing among others Cyber-Physical Systems (CPS), Internet of Things (IoT) and Artificial Intelligence (AI). Realizing smart factories according to the I40 vision requires intelligent human-to-machine and machine-to-machine communication. To achieve this communication, CPS along with their data need to be described and interoperability conflicts arising from various representations need to be resolved. For establishing interoperability, industry communities have created standards and standardization frameworks. Standards describe main properties of entities, systems, and processes, as well as interactions among them. Standardization frameworks classify, align, and integrate industrial standards according to their purposes and features. Despite being published by official international organizations, different standards may contain divergent definitions for similar entities. Further, when utilizing the same standard for the design of a CPS, different views can generate interoperability conflicts. Albeit expressive, standardization frameworks may represent divergent categorizations of the same standard to some extent, interoperability conflicts need to be resolved to support effective and efficient communication in smart factories. To achieve interoperability, data need to be semantically integrated and existing conflicts conciliated. This problem has been extensively studied in the literature. Obtained results can be applied to general integration problems. However, current approaches fail to consider specific interoperability conflicts that occur between entities in I40 scenarios. In this thesis, we tackle the problem of semantic data integration in I40 scenarios. A knowledge graphbased approach allowing for the integration of entities in I40 while considering their semantics is presented. To achieve this integration, there are challenges to be addressed on different conceptual levels. Firstly, defining mappings between standards and standardization frameworks; secondly, representing knowledge of entities in I40 scenarios described by standards; thirdly, integrating perspectives of CPS design while solving semantic heterogeneity issues; and finally, determining real industry applications for the presented approach. We first devise a knowledge-driven approach allowing for the integration of standards and standardization frameworks into an Industry 4.0 knowledge graph (I40KG). The standards ontology is used for representing the main properties of standards and standardization frameworks, as well as relationships among them. The I40KG permits to integrate standards and standardization frameworks while solving specific semantic heterogeneity conflicts in the domain. Further, we semantically describe standards in knowledge graphs. To this end, standards of core importance for I40 scenarios are considered, i.e., the Reference Architectural Model for I40 (RAMI4.0), AutomationML, and the Supply Chain Operation Reference Model (SCOR). In addition, different perspectives of entities describing CPS are integrated into the knowledge graphs. To evaluate the proposed methods, we rely on empirical evaluations as well as on the development of concrete use cases. The attained results provide evidence that a knowledge graph approach enables the effective data integration of entities in I40 scenarios while solving semantic interoperability conflicts, thus empowering the communication in smart factories

Towards a software infrastructure for district energy management

Nowadays ICT is becoming a key factor to enhance the energy optimization in our cities. At district level, real-time information can be accessed to monitor and control the energy distribution network. Moreover, the fine grain monitoring and control done at building level can provide additional information to develop more efficient control policies for energy distribution in the district. In this paper we present a distributed software infrastructure for district energy management, which aims to provide a digital archive of the city in which energetic information is available. Such information is considered as the input for a decision system, which aims to increase the energy efficiency by promoting local balancing and shaving peak loads. As case study, we integrated in our proposed cloud the heating distribution network in Turin and we present exploitable options based on real-world environmental data to increase the energy efficiency and minimize the peak reques

Interoperability for Industrial Internet of Things Based on Service-oriented Architecture

The new Industry 4.0 envisions a future for agile and effective integration of the physical operational technologies (OT) and the cyber information technologies (IT) as well as autonomous cooperation among them. However, the wide variety and heterogeneity of industrial systems and field devices -especially on the factory floor - increase integration complexity. To address these challenges, new technologies and concepts such as the Industrial Internet of Things (IIoT), Service-oriented Architecture (SoA), Semantic Technologies, Machine Learning and Artificial Intelligence are being introduced to the industrial environment. In this paper, we focus on how industrial automation systems and field devices can be integrated into the IIoT framework and coordinated to adapt to dynamic operating environment. Specifically, this paper proposed an interoperability solution that makes use of SoA and Semantic Technologies to achieve supervised coordination of IIoT application systems. To illustrate the potential of this approach, the Service-oriented Architecture-based Arrowhead Framework is used as the fundamental framework for the implementation of the approach.acceptedVersio

Service-oriented architecture for device lifecycle support in industrial automation

Dissertação para obtenção do Grau de Doutor em Engenharia Electrotécnica e de Computadores Especialidade: Robótica e Manufactura IntegradaThis thesis addresses the device lifecycle support thematic in the scope of service oriented industrial automation domain. This domain is known for its plethora of heterogeneous equipment encompassing distinct functions, form factors, network interfaces, or I/O specifications supported by dissimilar software and hardware platforms. There is then an evident and crescent need to take every device into account and improve the agility performance during setup, control, management, monitoring and diagnosis phases. Service-oriented Architecture (SOA) paradigm is currently a widely endorsed approach for both business and enterprise systems integration. SOA concepts and technology are continuously spreading along the layers of the enterprise organization envisioning a unified interoperability solution. SOA promotes discoverability, loose coupling, abstraction, autonomy and composition of services relying on open web standards – features that can provide an important contribution to the industrial automation domain. The present work seized industrial automation device level requirements, constraints and needs to determine how and where can SOA be employed to solve some of the existent difficulties. Supported by these outcomes, a reference architecture shaped by distributed, adaptive and composable modules is proposed. This architecture will assist and ease the role of systems integrators during reengineering-related interventions throughout system lifecycle. In a converging direction, the present work also proposes a serviceoriented device model to support previous architecture vision and goals by including embedded added-value in terms of service-oriented peer-to-peer discovery and identification, configuration, management, as well as agile customization of device resources. In this context, the implementation and validation work proved not simply the feasibility and fitness of the proposed solution to two distinct test-benches but also its relevance to the expanding domain of SOA applications to support device lifecycle in the industrial automation domain

From Machinery to Insights: A Comprehensive Data Acquisition Approach for Battery Cell Production

To ensure the widespread use of sustainably produced battery cells, further progress in research is needed. The transition to automated data acquisition is complicated by the technical complexity of industrial data acquisition. Existing software solutions also fall short in meeting usability, reproducibility, extensibility, and cost-effectiveness requirements for research-scale battery production lines. To address these gaps, this paper presents and evaluates a comprehensive data acquisition and collection solution for research-scale battery production lines. It offers a systematic overview of the industrial data acquisition process, focusing on gathering data from various existing machinery and utilizing the industry standard OPC UA protocol. Given the lack of existing solutions that meet the specified requirements, the paper introduces the "ProductionPilot" software as a solution. "ProductionPilot" is designed to provide an extensible platform with a user-friendly web interface. It enables users to select, structure, monitor, and export live production data delivered via OPC UA. The effectiveness of the proposed system is validated at the CELLFAB battery production research facility at eLab of RWTH Aachen university, demonstrating its capability for long-term data acquisition and the generation of digital shadows. By addressing the limitations of current data collection methods and providing a comprehensive solution, this research aims to facilitate the broader adoption of lithium-ion batteries in renewable energy applications

Machine Tool Communication (MTComm) Method and Its Applications in a Cyber-Physical Manufacturing Cloud

The integration of cyber-physical systems and cloud manufacturing has the potential to revolutionize existing manufacturing systems by enabling better accessibility, agility, and efficiency. To achieve this, it is necessary to establish a communication method of manufacturing services over the Internet to access and manage physical machines from cloud applications. Most of the existing industrial automation protocols utilize Ethernet based Local Area Network (LAN) and are not designed specifically for Internet enabled data transmission. Recently MTConnect has been gaining popularity as a standard for monitoring status of machine tools through RESTful web services and an XML based messaging structure, but it is only designed for data collection and interpretation and lacks remote operation capability. This dissertation presents the design, development, optimization, and applications of a service-oriented Internet-scale communication method named Machine Tool Communication (MTComm) for exchanging manufacturing services in a Cyber-Physical Manufacturing Cloud (CPMC) to enable manufacturing with heterogeneous physically connected machine tools from geographically distributed locations over the Internet. MTComm uses an agent-adapter based architecture and a semantic ontology to provide both remote monitoring and operation capabilities through RESTful services and XML messages. MTComm was successfully used to develop and implement multi-purpose applications in in a CPMC including remote and collaborative manufacturing, active testing-based and edge-based fault diagnosis and maintenance of machine tools, cross-domain interoperability between Internet-of-things (IoT) devices and supply chain robots etc. To improve MTComm’s overall performance, efficiency, and acceptability in cyber manufacturing, the concept of MTComm’s edge-based middleware was introduced and three optimization strategies for data catching, transmission, and operation execution were developed and adopted at the edge. Finally, a hardware prototype of the middleware was implemented on a System-On-Chip based FPGA device to reduce computational and transmission latency. At every stage of its development, MTComm’s performance and feasibility were evaluated with experiments in a CPMC testbed with three different types of manufacturing machine tools. Experimental results demonstrated MTComm’s excellent feasibility for scalable cyber-physical manufacturing and superior performance over other existing approaches

Machine Tool Communication (MTComm) Method and Its Applications in a Cyber-Physical Manufacturing Cloud

The integration of cyber-physical systems and cloud manufacturing has the potential to revolutionize existing manufacturing systems by enabling better accessibility, agility, and efficiency. To achieve this, it is necessary to establish a communication method of manufacturing services over the Internet to access and manage physical machines from cloud applications. Most of the existing industrial automation protocols utilize Ethernet based Local Area Network (LAN) and are not designed specifically for Internet enabled data transmission. Recently MTConnect has been gaining popularity as a standard for monitoring status of machine tools through RESTful web services and an XML based messaging structure, but it is only designed for data collection and interpretation and lacks remote operation capability. This dissertation presents the design, development, optimization, and applications of a service-oriented Internet-scale communication method named Machine Tool Communication (MTComm) for exchanging manufacturing services in a Cyber-Physical Manufacturing Cloud (CPMC) to enable manufacturing with heterogeneous physically connected machine tools from geographically distributed locations over the Internet. MTComm uses an agent-adapter based architecture and a semantic ontology to provide both remote monitoring and operation capabilities through RESTful services and XML messages. MTComm was successfully used to develop and implement multi-purpose applications in in a CPMC including remote and collaborative manufacturing, active testing-based and edge-based fault diagnosis and maintenance of machine tools, cross-domain interoperability between Internet-of-things (IoT) devices and supply chain robots etc. To improve MTComm’s overall performance, efficiency, and acceptability in cyber manufacturing, the concept of MTComm’s edge-based middleware was introduced and three optimization strategies for data catching, transmission, and operation execution were developed and adopted at the edge. Finally, a hardware prototype of the middleware was implemented on a System-On-Chip based FPGA device to reduce computational and transmission latency. At every stage of its development, MTComm’s performance and feasibility were evaluated with experiments in a CPMC testbed with three different types of manufacturing machine tools. Experimental results demonstrated MTComm’s excellent feasibility for scalable cyber-physical manufacturing and superior performance over other existing approaches

A Framework for Industry 4.0

The potential of the Industry 4.0 will allow the national industry to develop all kinds of procedures, especially in terms of competitive differentiation. The prospects and motivations behind Industry 4.0 are related to the management that is essentially geared towards industrial internet, to the integrated analysis and use of data, to the digitalization of products and services, to new disruptive business models and to the cooperation within the value chain. It is through the integration of Cyber-Physical Systems (CPS), into the maintenance process that it is possible to carry out a continuous monitoring of industrial machines, as well as to apply advanced techniques for predictive and proactive maintenance. The present work is based on the MANTIS project, aiming to construct a specific platform for the proactive maintenance of industrial machines, targeting particularly the case of GreenBender ADIRA Steel Sheet. In other words, the aim is to reduce maintenance costs, increase the efficiency of the process and consequently the profit. Essentially, the MANTIS project is a multinational research project, where the CISTER Research Unit plays a key role, particularly in providing the communications infrastructure for one MANTIS Pilot. The methodology is based on a follow-up study, which is jointly carried with the client, as well as within the scope of the implementation of the ADIRA Pilot. The macro phases that are followed in the present work are: 1) detailed analysis of the business needs; 2) preparation of the architecture specification; 3) implementation/development; 4) tests and validation; 5) support; 6) stabilization; 7) corrective and evolutionary maintenance; and 8) final project analysis and corrective measures to be applied in future projects. The expected results of the development of such project are related to the integration of the industrial maintenance process, to the continuous monitoring of the machines and to the application of advanced techniques of preventive and proactive maintenance of industrial machines, particularly based on techniques and good practices of the Software Engineering area and on the integration of Cyber-Physical Systems.O potencial desenvolvido pela Indústria 4.0 dotará a indústria nacional de capacidades para desenvolver todo o tipo de procedimentos, especialmente a nível da diferenciação competitiva. As perspetivas e as motivações por detrás da Indústria 4.0 estão relacionadas com uma gestão essencialmente direcionada para a internet industrial, com uma análise integrada e utilização de dados, com a digitalização de produtos e de serviços, com novos modelos disruptivos de negócio e com uma cooperação horizontal no âmbito da cadeia de valor. É através da integração dos sistemas ciber-físicos no processo de manutenção que é possível proceder a um monitoramento contínuo das máquinas, tal como à aplicação de técnicas avançadas para a manutenção preditiva e pró-ativa das mesmas. O presente trabalho é baseado no projeto MANTIS, objetivando, portanto, a construção de uma plataforma específica para a manutenção pró-ativa das máquinas industriais, neste caso em concreto das prensas, que serão as máquinas industriais analisadas ao longo do presente trabalho. Dito de um outro modo, objetiva-se, através de uma plataforma em específico, reduzir todos os custos da sua manutenção, aumentando, portanto, os lucros industriais advindos da produção. Resumidamente, o projeto MANTIS consiste num projeto de investigação multinacional, onde a Unidade de Investigação CISTER desenvolve um papel fundamental, particularmente no fornecimento da infraestrutura de comunicação no Piloto MANTIS. A metodologia adotada é baseada num estudo de acompanhamento, realizado em conjunto com o cliente, e no âmbito da implementação do Piloto da ADIRA. As macro fases que são compreendidas por esta metodologia, e as quais serão seguidas, são: 1) análise detalhada das necessidades de negócio; 2) preparação da especificação da arquitetura; 3) implementação/desenvolvimento; 4) testes e validação; 5) suporte; 6) estabilização; 7) manutenção corretiva e evolutiva; e 8) análise final do projeto e medidas corretivas a aplicar em projetos futuros. Os resultados esperados com o desenvolvimento do projeto estão relacionados com a integração do processo de manutenção industrial, a monitorização contínua das máquinas e a aplicação de técnicas avançadas de manutenção preventiva e pós-ativa das máquinas, especialmente com base em técnicas e boas práticas da área de Engenharia de Software